Özet:

This paper addresses control over flushing a well, which belongs to the class of non-stationary dynamic stochastic objects. The object evolves over time and has a large transport delay, which increases with an increase in the well's length. The current work is aimed at solving the tasks on improving a mathematical model of the automated control system taking into consideration a constraint on the capacity of a drilling pumping unit. The normalized transition functions of a pumping unit have been examined, based on which the magnitude of the delay has been determined, and the structures and parameters of typical controllers have been synthesized. It has been established that the only way to improve control quality is to use a more complex controller, which can reduce the negative impact of the delay. The closed automated control systems with delay have been investigated, which ensures better indicators of the control process compared to the industrial systems based on PI controllers. It has been shown that the Fuzzy-PID-controllers demonstrate better quality indicators – an overshooting of 0 % and a transition process duration of 15 s in a wide range of changes in the external influences and system parameters.An issue of the feasibility of applying the PI, PID-controllers with a Smith predictor has been considered. It has been shown that the quality of the control process involving a PID-controller and the Smith predictor is close to the quality indicators of the system with a Fuzzy-PID-controller. The need has been established to build a system that could independently adapt to changes in the geological and technical conditions and the geo-environment that occur in the process of deepening the well. It has been demonstrated that such systems should have a decision support circuit or be adaptive. The obtained data are useful and important because they make it possible to improve the efficiency of the control process of a technical hydraulic system of deep wells flushing during their deepening Author Biographies Andrii Lahoida, Ivano-Frankivsk National Technical University of Oil and Gas Karpatska str., 15, Ivano-Frankivsk, Ukraine, 76019 PhD, Associate Professor Department of Automation and Computer-Integrated Technology

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